What is real-world neuroscience?

Viewing a product on a screen, using it yourself and discussing it with someone are different research situations. Which situation fits the decision you need to make? Real-world neuroscience puts that question at the centre: how can you study the brain in relation to what people actually do and experience?

Here, real-world neuroscience is an umbrella term for studying people’s neural processes in everyday or purposefully realistic situations, with behaviour and context forming part of the research question. This working definition follows the real-life neuroscience approach discussed by Shamay-Tsoory and Mendelsohn (2019).

Examples include research during a visit, a workplace task or a conversation. A carefully recreated situation can also be relevant. The question is which features of everyday life you need to answer your research question.

The approach has several lines of development. This article does not identify a single publication as the origin of the broad term.

One concrete methodological foundation is mobile brain/body imaging, or MoBI: connecting brain recordings with body movements and information about the environment. Makeig and colleagues (2009) proposed wearable, integrated recording systems for this purpose.

Another line uses richer stimuli within a fixed recording environment. Hasson and colleagues (2004) used fMRI to investigate similarities in brain activity while participants watched the same film. This illustrates naturalistic material presented inside a scanner, without participants moving freely through an everyday environment.

Use concrete descriptions in your brief. In this article, we distinguish:

• Naturalistic research: using situations or materials that retain relevant features of everyday life, such as a continuous narrative.
• Mobile recording: a measurement setup that allows participants to move from place to place.
• Field research: research in the setting where the behaviour occurs, such as a shop or workplace.

These features can overlap, but do not have to coincide. Describe separately what a person sees, what they can do and where recording takes place. This helps establish whether a proposal adequately represents your intended use context.

The comparison below is an editorial planning aid, not a ranking of research quality.

You can combine designs. For example, investigate a focused question first and then plan a test in the intended use setting. Agree beforehand which outcome would justify that next step.

Ecological validity often refers to how research relates to everyday behaviour, but the term has different meanings. Holleman and colleagues (2020) argue for precise context descriptions rather than a general label of ‘realistic’.

Make the intended application concrete in your brief. Do you need to understand first-time visitors on a quiet morning, returning customers during busy periods or employees on their normal shift? Record which situation will be studied and which other situations will require further evidence.

Mobile EEG is one possible method within this approach. An early field study by Debener and colleagues (2012) examined an auditory task while participants walked outdoors. The authors reported usable P300 classification in that particular setup. This does not establish universal suitability for every headset or application.

Choose the method according to the information you need. Request a proposal explaining what a measurement adds to observations, task performance or interviews. For the basics, read [EEG explained](/en/knowledge-base/eeg-explained); for a focused application, read [EEG in experience research](/en/knowledge-base/eeg-experience-research).

A mobile recording gains meaning from the events around it. Within MoBI, Gramann and colleagues (2014) emphasise synchronised recording of actions, the environment and brain activity.

Ask the research team to demonstrate how it will identify a relevant moment: seeing an information sign, starting a conversation or picking up a product. Agree what recording is needed, what timing accuracy suits the analysis and how missing segments will be handled. Collect only the contextual information your question requires.

In research by Gwin and colleagues (2010), the influence of movement artefacts differed between walking and running conditions. The study tested a specific correction approach. It does not guarantee that every mobile recording can be made fully usable afterwards.

Include the intended actions in a pilot. Then ask which parts of the experience can be assessed with the chosen analysis. Allow room in the report for missing or insufficiently interpretable moments, so a design decision does not rest on an unanswered part of the journey.

Use these six questions as a practical briefing structure:

1. Which decision is central? Describe what you want to design, change or investigate further.
2. Which action do you want to understand? Specify what someone does, for what purpose and in which setting.
3. What should the recording add? Ask what additional information the chosen brain measurement can provide.
4. Which comparison is needed? Describe variants or conditions and discuss allocation and order.
5. What makes execution useful? Request a rationale for event recording, participant selection, data quality and analysis.
6. What will support the advice? Agree how measurement, interpretation, uncertainty and recommendations will be distinguished.

This structure is editorial guidance for a discussion. It is not a fixed Neurofactor protocol or a prescription for a particular participant number.

A visitor centre wants to know whether new signs help people find the correct room independently. The team considers evaluating sign designs first, followed by a route study using mobile EEG.

A useful proposal describes which route choices will be recorded, which task outcome matters most and which specific EEG analysis should provide additional insight. Plan a short debrief as well: where did the visitor hesitate, and what information were they looking for?

Suppose visitors follow the correct route more often with the new signs, while an EEG difference remains difficult to interpret. The report can discuss the navigation outcome without presenting it as a proven change in ‘unconscious stress’. The recommendation should identify which data support the design choice and which possible explanation still needs testing.

This is a fictional example. It does not describe a completed Neurofactor case or contain measured results.

When reviewing a proposal or report, ask:

• Which statement specifically concerns the participants and conditions studied?
• Which alternative explanation was considered before attributing a difference to the design?
• Was the meaning of a label such as ‘engagement’ defined and justified beforehand?
• Which expectation was tested in advance, and which observation is a new lead?
• What follow-up is needed before applying the recommendation to other locations?

Research can be useful without resolving every uncertainty. It should make clear what the outcome supports and what remains a working hypothesis.

Real-world neuroscience helps connect a research question with the circumstances in which an experience or action takes place. Start with your decision, choose the relevant situation and ask for a traceable analysis. You can then assess what recording on location adds and how to use the outcome in your design or strategy.